With the advent of multielectrode recordings and advanced computerized data collection systems, exceedingly large and complex datasets become increasingly obtainable. An important challenge for modern neuroscience is to develop new quantitative tools for the analysis and interpretation of large data sets recorded simultaneously from multiple neurons during specific behaviors. Whereas traditional techniques have focused on single-neuron spike trains, there is a growing recognition by the neuroscience community that the coordinated activity of multiple neurons, sometimes distributed across wide distances in the brain, is crucial for understanding the neural basis of higher brain functions. The central goal of this research project is to develop a sharable, extendable, open-source program package for the analysis of multielectrode recordings for the neuroscience research community. To attain this goal, we plan to develop and implement three technical projects and then test the feasibility of combining them in a single common graphical environment. First, we will build upon our previously developed comprehensive approach to the statistical quantification of neuronal activity on a fast time scale. We plan to reconstruct, test and optimize existing routines, and then wrap them into an easy-to-use menu-driven analysis desktop. We will demonstrate the feasibility and flexibility of this approach by the substantial improvement in usability of our software routines. Second, we will continue our methodological development by incorporating new analytic tools, including the causal inference measure and nonlinear techniques. This project is to demonstrate how to create new sharable, user-developed functions by taking advantage of our modular, user extensible software design. Third, the principled application of this package to multi-channel neuronal data recorded from both visuomotor integration and visual spatial attention tasks will demonstrate the feasibility of using the developed programs to address important questions in cognitive neuroscience. All three projects, together, provide support for our Phase I feasibility studies on the development of a sharable, extendable, open-source software package for the analysis and visualization of multielectrode neural data. At the completion of this project we expect to make available novel and well-tested digital signal processing tools for the investigation of large-scale neural systems in a variety of neurocognitive processes.